AMD Instinct MI308X GPU Accelerator

Brand: AMD | Category: GPUs

SKU: 100-300000076 | Part #: 100-300000076 | MPN: 100-300000076

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About the AMD Instinct MI308X GPU Accelerator

PCIe 5.0 x16 connectivity and 750 W TBP determine server chassis and power supply compatibility — critical factors for deployment planning. The AMD Instinct MI308X GPU Accelerator (part number 100-300000076) is a high-performance data center GPU built on AMD's CDNA 3 architecture and housed in an OAM (Open Accelerator Module) form factor. With 192 GB of HBM3 memory and 5.3 TB/s memory bandwidth, this accelerator delivers the compute density required for large-scale AI model training, inference, and scientific computing workloads. The 228 compute units provide peak performance metrics spanning FP64 vector operations at 163.4 TFLOPS, FP64 matrix operations at 326.8 TFLOPS, FP32 matrix operations at 653.7 TFLOPS, FP16/BF16 matrix operations at 1307.4 TFLOPS, and FP8 matrix operations at 2614.9 TFLOPS — enabling flexible precision tuning for diverse algorithmic requirements.

AMD ROCm serves as the open-source software platform, with native framework compatibility spanning PyTorch, TensorFlow, and JAX. This combination simplifies integration into existing enterprise data center, AI infrastructure, and HPC cluster environments. For AI infrastructure teams and procurement specialists evaluating GPU accelerators, the MI308X combines memory capacity with bandwidth efficiency and multi-precision compute performance to support transformer models, large language models, and simulation-based workloads. The PCIe 5.0 x16 interface ensures modern server interoperability while the 750 W power envelope fits standard enterprise data center power budgets. Contact Omnixon Global to request a detailed quotation for the AMD Instinct MI308X (100-300000076).

Typical Enterprise Deployment Scenarios

  • Large-scale model training and fine-tuning for generative AI applications
  • High-throughput inference serving in multi-tenant data centers
  • Scientific HPC simulations requiring sustained FP64 and FP32 compute
  • Financial modeling and risk analysis clusters demanding precision and memory bandwidth
  • Research institutions scaling deep learning workloads across accelerated clusters

Technical Specifications

BrandAMD
CategoryGPUs
SKU100-300000076
Part Number100-300000076
ConditionNew
Manufacturer Part Number100-300000076
Product NameAMD Instinct MI308X GPU Accelerator
ArchitectureAMD CDNA 3
Form FactorOAM (Open Accelerator Module)
Memory TypeHBM3
Memory Capacity192 GB
Memory Bandwidth5.3 TB/s
Peak FP64 Vector Performance163.4 TFLOPS
Peak FP64 Matrix Performance326.8 TFLOPS
Peak FP32 Matrix Performance653.7 TFLOPS
Peak FP16 / BF16 Matrix Performance1307.4 TFLOPS
Peak FP8 Matrix Performance2614.9 TFLOPS
Host InterfacePCIe 5.0 x16
Compute Units228
Total Board Power (TBP)750 W
Software PlatformAMD ROCm (open-source)
Framework CompatibilityPyTorch, TensorFlow, JAX (via ROCm)
Target DeploymentEnterprise data center, AI infrastructure, HPC clusters

Frequently Asked Questions about AMD Instinct MI308X GPU Accelerator

What does the AMD Instinct MI308X GPU Accelerator do?

The AMD Instinct MI308X GPU Accelerator accelerates AI/ML training, inference, scientific HPC, and virtualization (vGPU) workloads. Typical deployments include LLM training clusters, computer-vision pipelines, financial risk modeling, and rendering farms.

What are the headline specs of the AMD Instinct MI308X GPU Accelerator?

Key specifications for the AMD Instinct MI308X GPU Accelerator: new condition; gpu support AMD MI300X; ai optimized Yes. Manufacturer part number 100-300000076. For the full datasheet with electrical, environmental, and compliance details, contact our pre-sales engineering team.

Is the AMD Instinct MI308X GPU Accelerator compatible with my infrastructure?

The AMD Instinct MI308X GPU Accelerator requires a PCIe Gen4 or Gen5 x16 slot, server power adequate for the card's TDP, and CUDA/ROCm driver support in your hypervisor or bare-metal OS. Sales engineering will confirm chassis fit (1U/2U/4U), PCIe lane count, and PSU headroom before quoting.